The agent gathered enough information to write a credible overview of Well Kept's purpose, target audience, core features, and pricing model, but had to work around significant gaps in the site's own transparency. The homepage and /about page provided basic positioning; external comparison articles and web search filled in details about pricing tiers, competitors, and feature differentiation that the official site did not expose clearly. The site's navigation was sparse (404s on /pricing and /features), forcing heavy reliance on prior knowledge and third-party sources.

• ›Step [1] (homepage) and [9] (/about page) provided only high-level positioning—'home management for shared living'—without feature details, pricing, or competitor context. The /about page was discoverable only via web search, not from homepage navigation.
• ›Pricing information was not published on wellkeptapp.com at all. Steps [14] (realestateledger.io comparison) and [25] (getkeptapp.com blog) were external articles that mentioned Well Kept alongside competitors, allowing the agent to infer feature differentiation and rough pricing ($4.99/month Pro tier), but these were assembled from third-party sources, not official docs.
• ›The agent's final answer explicitly lists 'What Was Confusing or Missing': no dedicated /pricing page, vague free vs. Pro feature breakdown, limited third-party reviews, unclear Advisor details, no founder/company info easily accessible, and unclear platform availability (web/iOS/Android). These gaps reflect poor site structure and information architecture.
• ›The site forced the agent into a 'heavy bridge' pattern: direct fetches of official pages returned minimal structured information, so 7 of 13 web searches were necessary to supplement. The agent cited only the official site pages as sources in its final answer, but the substantive content came from external comparison articles that had aggregated Well Kept's features and positioning.
• ›Feature list (inventory, maintenance tracking, shared access, expense splitting, Advisor) was not found on any single official page, but was reconstructed from scattered homepage snippets and external articles. The agent had to synthesize across sources and rely on reasonable inference about how shared home management apps typically work.